{"id":5283,"date":"2016-08-26T00:58:37","date_gmt":"2016-08-25T16:58:37","guid":{"rendered":"http:\/\/people.utm.my\/haslinasarkan\/?p=5283"},"modified":"2016-08-25T14:02:05","modified_gmt":"2016-08-25T06:02:05","slug":"invitation-to-advanced-statistical-methods-for-big-data-analysis-of-neuroimaging","status":"publish","type":"post","link":"https:\/\/people.utm.my\/haslinasarkan\/invitation-to-advanced-statistical-methods-for-big-data-analysis-of-neuroimaging\/","title":{"rendered":"Invitation to \u201cAdvanced Statistical Methods for Big Data Analysis of Neuroimaging”"},"content":{"rendered":"

Pamphlet_shortcourse<\/a><\/p>\n

———————–\u00a0Short-Course Announcement\u00a0———————–<\/p>\n

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Advanced Statistical Methods for Big Data Analysis of Neuroimaging<\/p>\n

Applications to Brain Connectivity<\/p>\n

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Menara Razak<\/p>\n

Universiti Teknologi Malaysia, Kuala Lumpur Campus,<\/p>\n

Jalan Semarak, Kuala Lumpur.<\/p>\n

9th<\/sup>\u00a0Sept 2016 (Friday)<\/p>\n

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Speakers: Prof\u00a0Dr\u00a0Hernando Ombao<\/p>\n

Department of Statistics,\u00a0University\u00a0of California at Irvine, US<\/p>\n

Prof. Ir. Dr. Sheikh Hussain Shaikh Salleh and Dr. Chee-Ming Ting,<\/p>\n

Center for Center for Biomedical Engineering<\/p>\n

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Organizer: Center for Biomedical Engineering, Universiti Teknologi Malaysia.<\/p>\n

Advisor: Dato’ Prof Ir\u00a0Dr\u00a0Alias Mohd Noor<\/p>\n

Organizing Chair: Prof. Ir. Dr. Sheikh Hussain Shaikh Salleh<\/p>\n

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Dear Datuk\/Prof\/Dr\/Mr\/Mrs\/Miss,<\/p>\n

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We cordially invite you to a one-day short course entitled \u201cAdvanced Statistical Methods for Big Data Analysis of Neuroimaging Applications to Brain Connectivity\u201d which will be held on 9th<\/sup>\u00a0Sept 2016 (Friday) at Universiti Teknologi Malaysia, Kuala Lumpur.<\/p>\n

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This short course will introduce the fundamentals of a range of advanced statistical techniques for analyzing brain signals, in terms of modeling, estimation, inference and prediction of large neuroimaging data, e.g. functional magnetic resonance imaging (fMRI) and electroencephalogram (EEG) signals with state-of-the-art applications to brain connectivity analysis. Professor Hernando Ombao will present statistical exploratory approaches to modeling dependence between components of high-dimensional time series in designed experiments. These approaches could potentially impact neuroscience research that\u00a0focus\u00a0on functional connectivity between brain regions as a diagnostic marker for mental and neurological diseases and as a predictor\u00a0for\u00a0behavior. The major hurdle of high dimensionality in EEGs and fMRI will be addressed by using factor analysis and penalized regression such as LASSO method.<\/p>\n

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The course is organized into four lecture sections:<\/p>\n

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Session I and II: Prof Ombao will cover the following basic topics. These topics are essential to conducting a rigorous analysis of signals and to developing more sophisticated methods for modeling the complex features of the signals.<\/p>\n

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